MapReduce编程系列 — 2：计算平均分

标签：

1、项目名称：

2、程序代码：

package com.averagescorecount;

import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;


public class ScoreCount {
    /*这个map的输入是经过InputFormat分解过的数据集，InputFormat的默认值是TextInputFormat，它针对文件，
    *按行将文本切割成InputSplits，并用LineRecordReader将InputSplit解析成<key,value>对，
    *key是行在文本中的位置，value是文件中的一行。
    */
    public static class Map extends Mapper<LongWritable, Text, Text , IntWritable>{
        public void map(LongWritable key , Text value , Context context ) throws IOException, InterruptedException{
            String line = value.toString();
            System.out.println("line:"+line);

            System.out.println("TokenizerMapper.map...");
            System.out.println("Map key:"+key.toString()+" Map value:"+value.toString());
            //将输入的数据首先按行进行分割
            StringTokenizer tokenizerArticle = new StringTokenizer(line,"\n");
            //分别对每一行进行处理
            while (tokenizerArticle.hasMoreTokens()) {
                //每行按空格划分
                StringTokenizer tokenizerLine = new StringTokenizer(tokenizerArticle.nextToken());
                String strName = tokenizerLine.nextToken();//学生姓名部分
                String  strScore= tokenizerLine.nextToken();//成绩部分

                Text name = new Text(strName);
                int scoreInt = Integer.parseInt(strScore);

                 System.out.println("name:"+name+"  scoreInt:"+scoreInt);

                context.write(name, new IntWritable(scoreInt));
                System.out.println("context_map:"+context.toString());
            }            
             System.out.println("context_map_111:"+context.toString());
        }
    }

    public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable>{
            public void reduce(Text key , Iterable<IntWritable> values,Context context) throws IOException,InterruptedException{
                int sum = 0;
                int count = 0;
                int score = 0;
                System.out.println("reducer...");
                System.out.println("Reducer key:"+key.toString()+"  Reducer values:"+values.toString());
                //设置迭代器
                Iterator<IntWritable> iterator = values.iterator();
                while (iterator.hasNext()) {
                    score = iterator.next().get();
                    System.out.println("score:"+score);
                    sum += score;
                    count++;

                }
                int average = (int) sum/count;
                System.out.println("key"+key+"   average:"+average);
                context.write(key, new IntWritable(average));
                System.out.println("context_reducer:"+context.toString());
            }
    }

    public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = new Job(conf, "score count");
    job.setJarByClass(ScoreCount.class);

    job.setMapperClass(Map.class);
    job.setCombinerClass(Reduce.class);
    job.setReducerClass(Reduce.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);

    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

4、运行过程：

14/09/20 19:31:16 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
14/09/20 19:31:16 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
14/09/20 19:31:16 WARN mapred.JobClient: No job jar file set.  User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
14/09/20 19:31:16 INFO input.FileInputFormat: Total input paths to process : 1
14/09/20 19:31:16 WARN snappy.LoadSnappy: Snappy native library not loaded
14/09/20 19:31:16 INFO mapred.JobClient: Running job: job_local_0001
14/09/20 19:31:16 INFO util.ProcessTree: setsid exited with exit code 0
14/09/20 19:31:16 INFO mapred.Task:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@4080b02f
14/09/20 19:31:16 INFO mapred.MapTask: io.sort.mb = 100
14/09/20 19:31:16 INFO mapred.MapTask: data buffer = 79691776/99614720
14/09/20 19:31:16 INFO mapred.MapTask: record buffer = 262144/327680
line:陈洲立 67
TokenizerMapper.map...
Map key:0 Map value:陈洲立 67
name:陈洲立  scoreInt:67
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东伟 90
TokenizerMapper.map...
Map key:13 Map value:陈东伟 90
name:陈东伟  scoreInt:90
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:李宁 87
TokenizerMapper.map...
Map key:26 Map value:李宁 87
name:李宁  scoreInt:87
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:杨森 86
TokenizerMapper.map...
Map key:36 Map value:杨森 86
name:杨森  scoreInt:86
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东奇 78
TokenizerMapper.map...
Map key:46 Map value:陈东奇 78
name:陈东奇  scoreInt:78
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:谭果 94
TokenizerMapper.map...
Map key:59 Map value:谭果 94
name:谭果  scoreInt:94
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:盖盖 83
TokenizerMapper.map...
Map key:69 Map value:盖盖 83
name:盖盖  scoreInt:83
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈洲立 68
TokenizerMapper.map...
Map key:79 Map value:陈洲立 68
name:陈洲立  scoreInt:68
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东伟 96
TokenizerMapper.map...
Map key:92 Map value:陈东伟 96
name:陈东伟  scoreInt:96
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:李宁 82
TokenizerMapper.map...
Map key:105 Map value:李宁 82
name:李宁  scoreInt:82
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:杨森 85
TokenizerMapper.map...
Map key:115 Map value:杨森 85
name:杨森  scoreInt:85
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东奇 72
TokenizerMapper.map...
Map key:125 Map value:陈东奇 72
name:陈东奇  scoreInt:72
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:谭果 97
TokenizerMapper.map...
Map key:138 Map value:谭果 97
name:谭果  scoreInt:97
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:盖盖 82
TokenizerMapper.map...
Map key:148 Map value:盖盖 82
name:盖盖  scoreInt:82
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈洲立 46
TokenizerMapper.map...
Map key:158 Map value:陈洲立 46
name:陈洲立  scoreInt:46
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东伟 48
TokenizerMapper.map...
Map key:171 Map value:陈东伟 48
name:陈东伟  scoreInt:48
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:李宁 67
TokenizerMapper.map...
Map key:184 Map value:李宁 67
name:李宁  scoreInt:67
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:杨森 33
TokenizerMapper.map...
Map key:194 Map value:杨森 33
name:杨森  scoreInt:33
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:陈东奇 28
TokenizerMapper.map...
Map key:204 Map value:陈东奇 28
name:陈东奇  scoreInt:28
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:谭果 78
TokenizerMapper.map...
Map key:217 Map value:谭果 78
name:谭果  scoreInt:78
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:盖盖 87
TokenizerMapper.map...
Map key:227 Map value:盖盖 87
name:盖盖  scoreInt:87
context_map:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
line:
TokenizerMapper.map...
Map key:237 Map value:
context_map_111:org.apache.hadoop.mapreduce.Mapper$Context@d4cf771
14/09/20 19:31:16 INFO mapred.MapTask: Starting flush of map output
reducer...
Reducer key:李宁  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:82
score:87
score:67
key李宁   average:78
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:杨森  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:33
score:86
score:85
key杨森   average:68
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:盖盖  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:87
score:83
score:82
key盖盖   average:84
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:谭果  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:94
score:97
score:78
key谭果   average:89
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:陈东伟  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:48
score:90
score:96
key陈东伟   average:78
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:陈东奇  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:72
score:78
score:28
key陈东奇   average:59
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
reducer...
Reducer key:陈洲立  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@63dbbdf2
score:68
score:67
score:46
key陈洲立   average:60
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@3d32487
14/09/20 19:31:16 INFO mapred.MapTask: Finished spill 0
14/09/20 19:31:16 INFO mapred.Task: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
14/09/20 19:31:17 INFO mapred.JobClient:  map 0% reduce 0%
14/09/20 19:31:19 INFO mapred.LocalJobRunner:
14/09/20 19:31:19 INFO mapred.Task: Task ‘attempt_local_0001_m_000000_0‘ done.
14/09/20 19:31:19 INFO mapred.Task:  Using ResourceCalculatorPlugin : org.apache.hadoop.util.LinuxResourceCalculatorPlugin@5fc24d33
14/09/20 19:31:19 INFO mapred.LocalJobRunner:
14/09/20 19:31:19 INFO mapred.Merger: Merging 1 sorted segments
14/09/20 19:31:19 INFO mapred.Merger: Down to the last merge-pass, with 1 segments left of total size: 102 bytes
14/09/20 19:31:19 INFO mapred.LocalJobRunner:
reducer...
Reducer key:李宁  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:78
key李宁   average:78
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:杨森  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:68
key杨森   average:68
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:盖盖  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:84
key盖盖   average:84
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:谭果  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:89
key谭果   average:89
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:陈东伟  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:78
key陈东伟   average:78
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:陈东奇  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:59
key陈东奇   average:59
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
reducer...
Reducer key:陈洲立  Reducer values:org.apache.hadoop.mapreduce.ReduceContext$ValueIterable@2407325d
score:60
key陈洲立   average:60
context_reducer:org.apache.hadoop.mapreduce.Reducer$Context@52403ee2
14/09/20 19:31:19 INFO mapred.Task: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
14/09/20 19:31:19 INFO mapred.LocalJobRunner:
14/09/20 19:31:19 INFO mapred.Task: Task attempt_local_0001_r_000000_0 is allowed to commit now
14/09/20 19:31:19 INFO output.FileOutputCommitter: Saved output of task ‘attempt_local_0001_r_000000_0‘ to hdfs://localhost:9000/user/hadoop/score_output
14/09/20 19:31:20 INFO mapred.JobClient:  map 100% reduce 0%
14/09/20 19:31:22 INFO mapred.LocalJobRunner: reduce > reduce
14/09/20 19:31:22 INFO mapred.Task: Task ‘attempt_local_0001_r_000000_0‘ done.
14/09/20 19:31:23 INFO mapred.JobClient:  map 100% reduce 100%
14/09/20 19:31:23 INFO mapred.JobClient: Job complete: job_local_0001
14/09/20 19:31:23 INFO mapred.JobClient: Counters: 22
14/09/20 19:31:23 INFO mapred.JobClient:   Map-Reduce Framework
14/09/20 19:31:23 INFO mapred.JobClient:     Spilled Records=14
14/09/20 19:31:23 INFO mapred.JobClient:     Map output materialized bytes=106
14/09/20 19:31:23 INFO mapred.JobClient:     Reduce input records=7
14/09/20 19:31:23 INFO mapred.JobClient:     Virtual memory (bytes) snapshot=0
14/09/20 19:31:23 INFO mapred.JobClient:     Map input records=22
14/09/20 19:31:23 INFO mapred.JobClient:     SPLIT_RAW_BYTES=116
14/09/20 19:31:23 INFO mapred.JobClient:     Map output bytes=258
14/09/20 19:31:23 INFO mapred.JobClient:     Reduce shuffle bytes=0
14/09/20 19:31:23 INFO mapred.JobClient:     Physical memory (bytes) snapshot=0
14/09/20 19:31:23 INFO mapred.JobClient:     Reduce input groups=7
14/09/20 19:31:23 INFO mapred.JobClient:     Combine output records=7
14/09/20 19:31:23 INFO mapred.JobClient:     Reduce output records=7
14/09/20 19:31:23 INFO mapred.JobClient:     Map output records=21
14/09/20 19:31:23 INFO mapred.JobClient:     Combine input records=21
14/09/20 19:31:23 INFO mapred.JobClient:     CPU time spent (ms)=0
14/09/20 19:31:23 INFO mapred.JobClient:     Total committed heap usage (bytes)=408944640
14/09/20 19:31:23 INFO mapred.JobClient:   File Input Format Counters
14/09/20 19:31:23 INFO mapred.JobClient:     Bytes Read=238
14/09/20 19:31:23 INFO mapred.JobClient:   FileSystemCounters
14/09/20 19:31:23 INFO mapred.JobClient:     HDFS_BYTES_READ=476
14/09/20 19:31:23 INFO mapred.JobClient:     FILE_BYTES_WRITTEN=81132
14/09/20 19:31:23 INFO mapred.JobClient:     FILE_BYTES_READ=448
14/09/20 19:31:23 INFO mapred.JobClient:     HDFS_BYTES_WRITTEN=79
14/09/20 19:31:23 INFO mapred.JobClient:   File Output Format Counters
14/09/20 19:31:23 INFO mapred.JobClient:     Bytes Written=79

5、输出结果：

MapReduce编程系列 — 2：计算平均分

标签：

原文地址：http://www.cnblogs.com/yangyquin/p/5021157.html